• Journal of Biomedical Engineering Research
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• v.12 no.2
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• pp.89-98
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• 1991

This study is concerned on the automation for cell diagnosis which has better objectivity and speed of test than human beings. Diagnosis is on the basis of shape change of abnormal Cells. Used parameters are nucleus area, nucleus perimeter, nucleus shape, cytoplasm area, nucleus/cytoplsm ratio, which was obtained using image processing technics. A new mode method is proposed on the automatic threshold selection for superior process time compared with Otsu's. Contour of the cytoplasm of abnormal cell is obtained using me- dian filter and sorel operator. The mask to get only original shape of abnormal cells is formed uslng the contour filling algorithm. In the result the normal cells are separated from the abnormal cells and the abnormal cells can be distinguished through screwing of abnormal cell's image with reference data to judge abnormal cells. Owing to this study the number of inspections which the pathologists should examine will be decreased and the time for inspection will be shortened.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.29 no.6
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• pp.251-256
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• 2019

In the process of ZnO ceramic sintering at a temperature of 1385℃, higher than the normal sintering temperature, some grains were growth up to mm scale. When sintered at 1400℃ for 8 hours, the size of the grains that are not involved in the abnormal growth is as large as 30~40 ㎛, but the size of the abnormal grown grain reaches 1,000 ㎛, which is more than 10,000 times bigger in volume than the normal one within 8 hr growth. As a cause of rapid and abnormal grain growth, primary particle size distribution, compaction density variation within sample and doping of impurities could be considered. The primary particle size distribution could be considered main reason for abnormal grain growth but no solid evidence was obtained. Through the observation of the microstructure, it is presumed that the giant grains grow absorbing the neighbor grains through a grain rotation process.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.619-628
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• 2007

This study is devoted to suggesting the norm of detection abnormal users who are inferior to the other users in the recommender system compared with estimation accuracy. To select the abnormal users, we propose the pre-filtering method by using the preference ratings to the item rated by users. In this study, the experimental result shows the possibility of detecting the abnormal users before the process of preference estimation through the prediction algorithm. And It will be possible to improve the performance of the recommender system by using this detecting norm.

• Journal of the Korean Ceramic Society
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• v.32 no.2
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• pp.147-154
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• 1995

Abnormal grain growth behavior of BaTiO3 ceramics with controlling of particle size distribution of calcined powder was investigated. The particle size distribution was controlled by changing the calcining temperature or by using of classification and regrinding process. With broadening of the normallized size distribution in calcined powder, it showeda normal grain growth behavior in sintered body due to an increase of volume fraction of seed grain in the calcined powder. It was supposed that the seed grains could easily contact each other for the rapid grain growth during sintering process and resulted in fast switching-over from abnormal to normal grain growth stage.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.3
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• pp.76-82
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• 1999

This study was carried out to verify finding performance of dental diamond bur and investigate the possibility of AE application in density field. Work pieces were made of acryl and bovine respectively for the experiments in this study. Grinding test was conducted to get the data of grinding resistance and specific finding energy of low different types of diamond bur by using tool dynamometer. AE signal was acquired to verify grinding process in the AE measuring system. AErms value was increased as the grinding velocity and depth were increasing, but it decreased as the feed rate was increasing. The case of the small value of AE signal is due to abnormal grinding in D type diamond bur. By analyzing AErms start and finish time of grinding working, abnormal grinding state can be confined. Abnormal state can be found through the behavior of AE signal in the finding working. As a result, it is expected that forecast of abnormal state is possible using AE equipments under real time process.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.332-333
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• 2018

This paper presents an advanced abnormal over-current protection with $SuperFET^{(R)}$ 800V MOSFET in Flyback converter. In advanced abnormal over-current protection, digital pattern generator is proposed to detect a steep di/dt current condition when secondary rectifier diode or the transformer is shorted. If current sensing signal is larger than current limit during consecutive switching cycle, Gate signal will be stopped for 7 internal switching periods. If the abnormal over-current maintains pattern, the controller goes into protection mode. The Advanced over-current protection has been implemented in a 0.35um BCDMOS process (ON Semiconductor process).

• Steel and Composite Structures
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• v.18 no.5
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• pp.1177-1195
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• 2015

Six specimens are tested to investigate the cyclic behavior of beam-to-column abnormal joints in steel moment-resisting frames, which are designed according to the principle of strong-member and weak-panel zone. Key parameters include the axial compression ratio of column and the section depth ratio of beams. Experimental results indicate that four types of failure patterns occurred during the loading process. The $P-{\Delta}$ hysteretic loops are stable and plentiful, but have different changing tendency at the positive and negative direction in the later of loading process due to mechanical behaviors of specimens. The ultimate strength tends to increase with the decrease of the section depth ratio of beams, but it is not apparent relationship to the axial compression ratio of column, which is less than 0.5. The top panel zone has good deformation capacity and the shear rotation can reach to 0.04 rad. The top panel zone and the bottom panel zone don't work as a whole. Based on the experimental results, the equation for shear strength of the abnormal joint panel zone is established by considering the restriction of the bottom panel zone to the top panel zone, which is suitable for the abnormal joint of H-shaped or box column and beams with different depths.

• Journal of Information Processing Systems
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• v.4 no.3
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• pp.113-120
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• 2008

Most enterprises have controlled claim data related to marketing, production, trade and delivery. They can extract the engineering information needed to the reliability of unit from the claim data, and also detect critical and latent reliability problems. Existing method which could detect abnormal quality unit lists in early stage from claim database has three problems: the exclusion of fallacy probability in claim, the false occurrence of claim fallacy alarm caused by not reflecting inventory information and too many excessive considerations of claim change factors. In this paper, we propose a process and methods extracting abnormal quality unit lists to solve three problems of existing method. Proposed one includes data extraction process for reliability measurement, the calculation method of claim fallacy alarm probability, the method for reflecting inventory time in calculating claim reliability and the method for identification of abnormal quality unit lists. This paper also shows that proposed mechanism could be effectively used after analyzing improved effects taken from automotive company's claim data adaptation for two years.

• Journal of Sericultural and Entomological Science
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• v.13 no.1
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• pp.61-67
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• 1971

This experiment was conducted to know the effects of abnormal cocoons on the silk quality during the silk reeling process. The results obtained are summarized as follows: 1. The length, the width, the weight, the layer weight, and the layer ratio of abnormal cocoons are in every case 0.83∼4.65% less than those of normal cocoons. 2. The thickness of the abnormal cocoon layer is at)out 20.62∼22.4% less than that of the normal cocoon. 3. The sericin solubility of tile abnormal cocoon layer is about 11.75∼30% more than that of the normal cocoon layer. 4. The degumming ratio of the abnormal cocoon layer is about 6.51∼9.32% more than that of the normal cocoon layer. 5. The length of a have, the weight of a tave and percentage of raw silk yield of the abnormal cocoon are decreased 9.43%, 8.53% and 6.72% each as compared with those of the normal cocoon. 6. The percentage of reelability of abnormal cocoons is decreased 9.58％ as compared with that of normal cocoons. 7. The neatness of abnormal cocoons is 3 per cent lower than that of normal cocoons. 8. In the cleanness test of abnormal cocoons, the number of split ends i9 about 1.5∼3.8 times as much as that of normal cocoons. Especially cleanness of abnormal cocoons is 16,3 per cent lower than that of normal cocoons. 9. The number of non-reelable cocoons of abnormal cocoons is increased 1.4∼5.5 times as much as that of normal cocoons. In abnormal cocoon, the number of knot which resulted in the breaking of silk end is increased 1.9∼3.5 times as much as that in normal cocoon.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.53-69
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• 2003

Many process variables in modem manufacturing processes have influence on quality of products with complicated relationships. Therefore, it is necessary to control multiple quality variables in order to monitor abnormal signals in the processes. This study proposes an integrated procedure of self-organizing map (SOM) neural network and case-based reasoning (CBR) for multivariate process control. SOM generates patterns of quality variables. The patterns are compared with the reference patterns in order to decide whether their states are normal or abnormal using the goodness-of-fitness test. For validation, it generates artificial datasets consisting of six patterns, normal and abnormal patterns. Experimental results show that the abnormal patterns can be detected effectively. This study also shows that the CBR procedure enables to keep Type 2 error at very low level and reduce Type 1 error gradually, and then the proposed method can be a solution fur multivariate process control.